As a consequence, more exact models of devices can
be retained for analysis rather than the approximate models commonly introduced
for the sake of computational simplicity. A computer icon appears in the margin
with each introduction of MATLAB analysis.
As a consequence, more exact models of devices can
be retained for analysis rather than the approximate models commonly introduced
for the sake of computational simplicity. A computer icon appears in the margin
with each introduction of MATLAB analysis.
As a consequence, more exact models of devices can
be retained for analysis rather than the approximate models commonly introduced
for the sake of computational simplicity. A computer icon appears in the margin
with each introduction of MATLAB analysis.
As a consequence, more exact models of devices can
be retained for analysis rather than the approximate models commonly introduced
for the sake of computational simplicity. A computer icon appears in the margin
with each introduction of MATLAB analysis.
As a consequence, more exact models of devices can
be retained for analysis rather than the approximate models commonly introduced
for the sake of computational simplicity. A computer icon appears in the margin
with each introduction of MATLAB analysis.
A Matlab toolbox for exact linear time-invariant system identification is presented. The emphasis is on the variety of possible ways to implement the mappings from data to parameters of the data generating system. The considered system representations are input/state/output, difference equation, and left matrix fraction.
KEYWORDS: subspace identification, deterministic subspace identification, balanced model reduction, approximate system identification, MPUM.
